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PEMROSESAN DAN KLASIFIKASI SINYAL DENGAN METODE ORTHOGONAL MATCHING PURSUIT DAN CONVOLUTIONAL NEURAL NETWORK TERHADAP SINYAL BAHASA ISYARAT PADA RADAR DOPPLER.

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At this time, the development of radar technology has experienced quite rapid developments. The use of radar can now be used to detect body movement using sign language and represent it in the form of a signal so that it can be sent via telecommunications networks to other places. However, in telecommunications networks there are limitations regarding the amount of information that can be sent so that the information must go through several process stages such as compression of information data so that a reconstruction process is needed to restore the signal. In this research, the author used MatLab software to process the information data signals using the OMP method which was then classified using the CNN method. Tests were carried out using Doppler radar with conditions blocked by walls and without blocked walls and at varying distances ranging from 1m, 2m, 3m, 4m, 5m, and 6m to obtain information data signals from sign language movements which were then processed in MatLab software. From the test results in this research, it was found that the performance parameters when processing using the OMP method in conditions without obstructions had good results with an average SNR value of 34 dB and an average MSE value of 0.561%. Furthermore, when classifying using the CNN method, an MSE value of 13.89% was obtained or a classification success rate of 86.11%.

Availability
Inventory Code Barcode Call Number Location Status
2407000417T137872T1378722023Central Library (REFERENS)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1378722023
Publisher
Inderalaya : Prodi Teknik Elektro, Fakultas Teknik Universitas Sriwijaya.,
Collation
xxii, 94 hlm.;ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
621.382 07
Content Type
Text
Media Type
unmediated
Carrier Type
-
Edition
-
Subject(s)
Prodi Teknik Elektro
signal processing/sinyal
Specific Detail Info
-
Statement of Responsibility
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No other version available

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